# Note: this is an example sequence of commands I might run in ipython
# The matplotlib windows may not open/close properly if you run this directly as a script
import vlbi_imaging_utils as vb
import maxen as mx
import numpy as np
# Load the image and the array
#im = vb.load_im_fits('./models/avery_sgra_eofn.fits') #for a fits image
im = vb.load_im_txt('./models/avery_sgra_eofn.txt') #for a text file
eht = vb.load_array('./arrays/EHT2017.txt') #see the attached array text file
# Look at the image
im.display()
# Observe the image
# tint_sec is the integration time in seconds, and tadv_sec is the advance time between scans
# tstart_hr is the GMST time of the start of the observation and tstop_hr is the GMST time of the end
# bw_hz is the bandwidth in Hz
# sgrscat=True blurs the visibilities with the Sgr A* scattering kernel for the appropriate image frequency
# ampcal and phasecal determine if gain variations and phase errors are included
tint_sec = 60
tadv_sec = 600
tstart_hr = 0
tstop_hr = 24
bw_hz = 4e9
obs = im.observe(eht, tint_sec, tadv_sec, tstart_hr, tstop_hr, bw_hz, sgrscat=False, ampcal=False, phasecal=False)
# You can deblur the visibilities by dividing by the scattering kernel if necessary
#obs = vb.deblur(obs)
import vlbi_imaging_utils as vb
import maxen as mx
import numpy as np
import stochastic_optics as so
import vlbi_plots as vp
#observing parameters
tint_sec = 1e5
tadv_sec = 300
tstart_hr = 0.5
tstop_hr = 4.2
bw_hz = 0.5e9
# Load the image and the array
im = vb.load_im_txt('./models/avery_sgra_eofn.txt') #for a text file like the one attached
eht = vb.load_array('./arrays/EHT2017.txt') #see the attached array text file
# If the image has an odd number of pixels, make it even
if im.xdim%2 == 0:
newim = im.imvec.reshape(im.ydim, im.xdim)
newim = newim[:-1,:-1]
im = vb.Image(newim, im.psize, im.ra, im.dec, rf=im.rf, source=im.source, mjd=im.mjd)
# Generate an image prior
obs = im.observe(eht, tint_sec, tadv_sec, tstart_hr, tstop_hr, bw_hz, sgrscat=False, ampcal=True, phasecal=True)
npix = im.psize*(im.xdim-1.0)/im.xdim
npix = 101 #This must be odd
fov = 1.0*im.xdim * im.psize
zbl = np.sum(im.imvec) # total flux
emptyprior = vb.make_square(obs, npix, fov)
import vlbi_imaging_utils as vb
import maxen as mx
import numpy as np
im = vb.load_im_txt('./models/avery_sgra_eofn.txt')
arr = vb.load_array("./arrays/EHT2017_wKP_wRedundant.txt")
tint = 120
tadv = 600
bw = 4e9
obs = im.observe(arr, tint, tadv, 0, 24.0, bw, ampcal=False, phasecal=False, sgrscat=False)
# Generate an image prior
npix = 64
fov = 1.0 * im.xdim*im.psize #160.0*vb.RADPERUAS
zbl = 1.0 # total flux
prior_fwhm = 80*vb.RADPERUAS # Gaussian size in microarcssec
emptyprior = vb.make_square(obs, npix, fov)
flatprior = vb.add_flat(emptyprior, zbl)
gaussprior = vb.add_gauss(emptyprior, zbl, (prior_fwhm, prior_fwhm, 0, 0, 0))
beamparams = obs.fit_beam()
res = 1 / np.max(obs.unpack('uvdist')['uvdist'])
print beamparams
print res
out_cl = mx.maxen_onlyclosure(obs, gaussprior, flux = 1.0, maxit=50, alpha_clphase=10, alpha_clamp=10, gamma=500, delta=1e10, entropy="simple", stop=1e-15, grads=True)
out_cl = mx.maxen_onlyclosure(obs, mx.blur_circ(out_cl, 1e-10), flux = 1.0, maxit=100, alpha_clphase=10, alpha_clamp=10, gamma=500, delta=1e10, entropy="tv", stop=1e-10, grads=True)
out_cl = mx.maxen_onlyclosure(obs, mx.blur_circ(out_cl, 1e-10), flux = 1.0, maxit=100, alpha_clphase=5, alpha_clamp=5, gamma=500, delta=1e10, entropy="tv", stop=1e-10, grads=True)
out_cl = mx.maxen_onlyclosure(obs, mx.blur_circ(out_cl, 1e-10), flux = 1.0, maxit=100, alpha_clphase=5, alpha_clamp=5, gamma=500, delta=1e10, entropy="tv", stop=1e-10, grads=True)
out_cl = mx.maxen_onlyclosure(obs, mx.blur_circ(out_cl, 1e-10), flux = 1.0, maxit=100, alpha_clphase=5, alpha_clamp=5, gamma=500, delta=1e10, entropy="tv", stop=1e-10, grads=True)
